Curai - Member of Technical Staff, AI/ML
Requirements
• Hands-on experience building and deploying machine learning systems including generative AI (LLMS) , — and a clear track record of impact. • Strong software engineering fundamentals and the ability to ship reliable, well-tested code in Python (or a comparable language) in a production environment. • Practical understanding of modern LLM techniques: prompting, retrieval-augmented generation, fine-tuning, evaluation, and the trade-offs between them. • Comfort working with messy, real-world data and designing evaluations to know whether a system is actually working. • Strong written and verbal communication; ability to collaborate with clinicians, product managers, and engineers across disciplines. • A bias toward action and ownership: you can take an ambiguous problem, drive it to a result, and bring others along. • Care for the mission. You want your work to translate into better health outcomes for real patients. • Experience applying ML or LLMs in healthcare, life sciences, or another regulated, high-stakes domain. • Experience with clinical NLP, medical knowledge representation, or working with electronic health record data. • Experience building agentic systems, tool-using LLMs, in production. • Experience scaling ML infrastructure — training pipelines, distributed inference, evaluation platforms — for a small, fast-moving team. • Track record of technical leadership: setting direction across teams, mentoring engineers, or publishing influential work.
Responsibilities
• Design, build, train, evaluate and improve advanced machine learning and LLM-based systems for for patient and provider-facing products (e.g., conversational AI, personalization, user understanding, clinical decision support, chronic care management). • Own problems end-to-end: scope the problem with clinicians and product partners, build datasets and evaluations, iterate on modeling, and ship to production with the right monitoring and guardrails. • Develop robust evaluation frameworks — offline benchmarks, human-in-the-loop review, online experiments — that give us confidence our models are safe, accurate, and improving over time. • Build and improve the platform that lets the team move quickly: data pipelines, training and inference infrastructure, prompt and model management, and tooling for clinical reviewers. • Partner closely with clinicians, product, and engineering to translate medical and operational requirements into ML problems and ship measurable improvements to patient and clinician experience. • Set technical direction for your area, mentor other engineers, and raise the bar on engineering and scientific rigor. The scope of leadership scales with seniority. • Stay close to the literature and the rapidly evolving AI ecosystem; bring back what is most useful for our patients and our team.
Benefits
• High ownership work on problems that matter, with a tight feedback loop from real clinicians and patients. • A small, senior team where your work shows up in the product quickly. • Competitive compensation, meaningful equity, and comprehensive benefits. • Remote-first, flexible work environment across the U.S. • $180,000 - $280,000 a year • The pay range listed for this position is in the range the organization reasonably and in good faith expects to pay for this position at the time of the posting. The actual base salary offered will depend on a variety of factors, including the qualifications of the individual applicant for the position and years of relevant experience. In addition to base salary, this role is eligible for a competitive benefits package including comprehensive medical/dental/vision coverage, 401K employer match.
Apply in one click
Upload My Resume
Drop here or click to browse · Tap to choose · PDF, DOCX, DOC, RTF, TXT